Abstract
This chapter presents the environmental visual recognition method. A detailed presentation of the proposed method for extraction of 3D geometric-primitives is provided. The synergistic cue integration (homogeneity, edge and phase rim) for extraction of 2D geometric-primitives is presented. The consolidation of 3D geometric-primitives by calibrated stereo vision is introduced. The effectiveness and precision of the proposed method are experimentally evaluated with various natural and artificial illuminations on different environmental objects ranging from rather simple doors up to complex electric appliances.
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Notes
- 1.
Demosaicing is the reconstruction of a color image based on partial color samples from a sensor using a color filter array such as the wide spread Bayer pattern.
- 2.
Factorized as a sum in the exponent of \(A_G(\mathbf x ,\mathbf x _i)\) in Eq. 5.1.
- 3.
Minimum object distance is the shortest distance between the lens and the subject.
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González Aguirre, D.I. (2019). Environmental Visual Object Recognition. In: Visual Perception for Humanoid Robots. Cognitive Systems Monographs, vol 38. Springer, Cham. https://doi.org/10.1007/978-3-319-97841-3_5
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